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library(tidycensus)
library(tidyverse)
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(leaflet)
library(sf)
Linking to GEOS 3.12.2, GDAL 3.9.3, PROJ 9.4.1; sf_use_s2() is TRUE
library(viridis)
Loading required package: viridisLite
fl_education_data <- get_acs(
  geography = "tract",  # You can also use "tract" or "block group" for more granularity
  variables = "B15003_022",  # Less than 9th grade education
  state = "FL",  # Florida
  year = 2021,  # Specify the year of the ACS data
  survey = "acs5",  # 5-year ACS estimates
  geometry = TRUE  # Set to TRUE if you want spatial data
)
Getting data from the 2017-2021 5-year ACS
Warning: • You have not set a Census API key. Users without a key are limited to 500
queries per day and may experience performance limitations.
ℹ For best results, get a Census API key at
http://api.census.gov/data/key_signup.html and then supply the key to the
`census_api_key()` function to use it throughout your tidycensus session.
This warning is displayed once per session.
Downloading feature geometry from the Census website.  To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.

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fl_education_data$estimate <- as.numeric(fl_education_data$estimate)


fl_education_data <- fl_education_data[!st_is_empty(fl_education_data$geometry), ]
# Create a color palette based on the estimate values
pal <- colorNumeric(
  palette = viridis(10),  # Use the viridis color scale
  domain = fl_education_data$estimate  # Map to the estimate values
)
# Create the interactive map
leaflet_map <- leaflet(fl_education_data) %>%
  addTiles() %>%  # Add base map tiles
  addPolygons(
    fillColor = ~pal(estimate),  # Color polygons based on estimate
    fillOpacity = 0.7,  # Set polygon fill opacity
    color = "#444444",  # Border color
    weight = 1,  # Border width
    smoothFactor = 0.5,  # Smoothness of polygons
    popup = ~paste(  # Add popup with details
      "Census Tract: ", NAME, "<br>",
      "Population with <9th Grade Education: ", estimate
    )
  ) %>%
  addLegend(
    pal = pal,  # Use the color palette
    values = ~estimate,  # Map to estimate values
    title = "Population with <9th Grade Education",  # Legend title
    position = "bottomright"  # Legend position
  )
Warning: sf layer has inconsistent datum (+proj=longlat +datum=NAD83 +no_defs).
Need '+proj=longlat +datum=WGS84'
# Display the map
leaflet_map